posted on 2022-03-28, 19:25authored byErfan Khordad
Designing the beamforming vectors for channel estimation in mmWave systems is challenging becauseof the narrow beams required and the small number of useful directions. The state of the art employs random or structured random beamforming to leverage compressive sensing techniques to solve this problem using a small number of measurements. In this dissertation, inspired by existing deterministic sensing matrices from the theory of compressive sensing, two novel deterministic compressive sensing approaches are proposed for channel estimation in mmWave systems. In the proposed approaches, the Kronecker product or row-by-row Kronecker product of existing deterministic sensing matrices are used to design the structure of pilot beam patterns for the beam alignment process. These approaches not only result in significant overhead reduction, but also present improvement in terms of performance for some scenarios.
History
Table of Contents
1. Introduction -- 2. An overview of compressive sensing -- 3. System model -- 4. Pilot beam pattern design -- 5. Simulation results -- 6. Conclusion -- References.
Notes
Bibliography: pages 50-54
Empirical thesis.
Awarding Institution
Macquarie University
Degree Type
Thesis MRes
Degree
MRes, Macquarie University, Faculty of Science and Engineering, School of Engineering